https://doi.org/10.2352/ISSN.2470-1173.2018.17.AVM-146© 2018, Society for Imaging Science and Technology

LED flicker: Root cause, impact and measurement for automotive imaging applications
Brian Deegan; Valeo Vision Systems, Tuam, Galway, Ireland

Abstract
In recent years, the use of LED lighting has become
widespread in the automotive environment, largely because of
their high energy efficiency, reliability, and low maintenancecosts. There has also been a concurrent increase in the use andcomplexity of automotive camera systems. To a large extent, LED
lighting and automotive camera technology evolved separately
and independently. As the use of both technologies has increased,
it has become clear that LED lighting poses significant challenges
for automotive imaging i.e. so-called ”LED flicker”. LED flicker
is an artifact observed in digital imaging where an imaged lightsource appears to flicker, even though the light source appears
constant to a human observer. This paper defines the root cause
and manifestations of LED flicker. It defines the use cases where
LED flicker occurs, and related consequences. It further defines atest methodology and metrics for evaluating an imaging systems
susceptibility to LED flicker.

varying duty cycle (i.e. the fraction of one period when the lightis active) in order to adjust their apparent brightness. At frequencies greater than 90Hz, the light will usually appear to be constant
to most human observers [1, 2]. However, a camera imaging thelight source may require a very short exposure time to capture ascene correctly, particularly in bright conditions. An illustrative
example is shown in Figure 1. In frame N, the camera exposure
time coincides with a pulse from the PWM driven LED traffic
light. Therefore, for frame N, the red traffic light will be capturedby the camera. However, in frame N+1, the camera exposure timeand LED pulse do not coincide. In this case, the red light will
not be captured. Over the course of consecutive video frames,
the traffic light will appear to flicker on and off, depending onwhether or not the cameras exposure time coincides with the LED
light pulses.

Introduction
In recent years, the use of Pulse Width Modulation (PWM)
driven LED lighting has become widespread in the automotive
environment. Vehicle designers have taken advantage of the flexibility of LED headlamps to devise innovative styling designs,
which have now become a key brand differentiator. LED lighting
is also increasingly used in road signage and advertising, becauseof their high energy efficiency, reliability, and low maintenancecosts. There has also been a concurrent increase in the use ofcameras in the automotive industry. Automotive cameras have
evolved from simple backup cameras to advanced surround view
systems, mirror replacement systems, and machine vision cameras that enable Advanced Driver Assistance Systems (ADAS)
and autonomous driving. Automotive cameras themselves havealso evolved at a rapid pace, from simple low resolution cameras to advanced, high resolution High Dynamic Range (HDR)
cameras. To a very large extent, LED lighting and automotive
camera technology evolved separately and independently. As theuse of both technologies became widespread, it has become clearthat the increasing ubiquity of PWM driven LED lighting is posing significant challenges for automotive imaging i.e. so-called”LED flicker”. LED flicker is an artifact observed in digital imaging where a light source or a region of an imaged scene appears
to flicker (i.e. the light may appear to switch on and off or modulate in terms of brightness or colour), even though the light source
appears constant to a human observer.

Root cause
LED flicker is, in essence, a temporal sampling problem. It
occurs when a light source is being powered by a modulated signal. LED lights may pulse several hundred times a second with
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Figure 1. LED flicker root cause. In frame N, the LED pulse and the camera
exposure time coincide, and the traffic light is captured. In frame N+1, theLED pulse and exposure time do not coincide, and the traffic light appears
offMore specifically, a pulsed light source will flicker on/off if
the exposure time of the camera is less than the reciprocal of thefrequency of the light source i.e.
Texp ≤1∗ (1 − PW Mdutycycle )PW M f req(1)

where Texp is the exposure time of the camera, PWMfreq isthe frequency of the pulsed illumination, and PWMduty cycle is theduty cycle of the pulsed illumination, where 1.0 corresponds to100% duty cycle. A real world example is shown in Figure 2.
A second manifestation of flicker occurs when the numberof pulses captured varies from frame to frame. For example, if

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shutter sensor, the brightness of the entire scene will vary between
exposures. However, if a rolling shutter sensor is used, banding
effects will be visible. These banding artifacts have both a spatial
and temporal component. An example of this banding artifact isshown in Figure 4.

Figure 2. Example of flicker from directly imaged light source

you consider two consecutive video image captures, in frame N,
the camera exposure may capture one pulse from the light source,
whereas in the second frame, the camera exposure may capture
two pulses from the light source. Consequently, the brightnesslevel in the captured image varies between exposures. This is
illustrated in Figure 3:

Figure 4.

Example of banding artifact. This image was captured with arolling shutter sensor. In this example, the scene is illuminated by a diffuse
LED light source, driven by a 75Hz, 10% duty cycle signal

HDR imaging

Figure 3.

In this example, the number of captured pulses varies between

frame N and frame N+1. As a result, the brightness of the traffic light varies
between framesThis use case occurs when the exposure time of the camera
is greater than or equal to the frequency of the pulsed illuminationi.e.
Texp ≥1∗ (1 − PW Mdutycycle )PW M f req(2)

In this condition, the image light will never appear ”OFF”,
but the luma/chroma will modulate. Also, the manifestation of
the modulation varies, depending on the scene. In the case of
directly imaged light sources, the luma/chroma of the light will
modulate from frame to frame. The artifact is primarily temporalin nature. However, in the case where a scene is illuminated by apulsed light source, the observed artifact depends on the characteristics of the image sensor. If the scene is imaged by a global

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There are also specific artifacts caused by HDR imaging ofpulsed light sources. HDR imaging is quite common in automotive applications. This is because the dynamic range of many automotive scenes can be 120dB or more [3, 4]. This is beyond the
dynamic range of standard image sensors. The majority of automotive HDR image sensors use one form or other of multi-image
capture scheme. This is largely because multi-capture schemes
typically offer the best overall trade-off between dynamic range
extension and overall image quality, with minimal changes tothe pixel and sensor design. Multi-capture HDR schemes also
cause specific artifacts when imaging pulsed light sources. In very
bright scenes (e.g. bright daylight), PWM flicker will likely appear the same as for a standard image sensor. This is illustrated
in Figure 5. In this case, for frame N, all input captures may
be shorter than the ”OFF” time of the pulsed light. However, inframe N+1, the LED light pulse coincides with the long exposure
time, and is captured in the final output image.
In darker scenes, however, multi-capture schemes exhibit adifferent behaviour, as can be seen in Figure 6. In this example, inframe N, the L capture uses a significantly longer exposure time,
to capture details in the dark. As a result, it captures multiple
LED pulses, and may overexpose. However, the M capture misses
the pulse, and so is under-exposed. When the input images are
combined, it is often the case that the over-exposed image L ismerged with the underexposed image M, and the combined output
is medium grey combination with no detail. In frame N+1, theLED pulse is captured by both the L and M captures. In this case,the merged HDR output captures the image correctly.
A real-life example of this effect is shown in Figure 7. In
frame N, the sign on the bus is overexposed in the long exposure
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Figure 5.

Illustrative example of multi-capture HDR scheme in brightscenes. L=long exposure time capture, M=medium exposure time capture,
S=short exposure time capture. In this example, all three input images areshorter than the ”OFF” period of the light pulse in frame N. In frame N+1, theLED pulse coincides with the long exposure, and so is included in the output
HDR image. The result is that the traffic light pulses on and off

Figure 7. Example of HDR PWM flicker in lowlight scene. Two consecutive
frames from a video sequence are shown. The sign is driven by a PWM
signal. In frame N (top), the bus sign is captured only by the long exposureand missed by the short exposure. The combined output is a mid-grey artifact
with no detail. In frame N+1 (bottom), the bus sign is captured by the short
exposure, and is therefore reproduced correctly in the combined HDR output
image
Figure 6. Illustrative example of multi-capture HDR scheme in dark scenes.
L=long exposure time capture, M=medium exposure time capture, S=short
exposure time capture. In this example, in frame N, the L capture uses a
significantly longer exposure time, to capture details in the dark. As a result,it captures multiple LED pulses, and may overexpose. However, the M capture misses the pulse, and so is underexposed. When the input images are
combined, it is often the case that the over-exposed image L is merged withthe underexposed image M, and the combined output is medium grey combination with no detail. In frame N+1, the LED pulse is captured by both the
L and M captures. In this case, the merged HDR output captures the image
correctly

image, and underexposed in the short capture image. The merged
HDR output is flat grey, with no detail. In frame N+1, the bus
sign is captured by the short exposure capture, and is therefore
reproduced correctly in the output image.

Impact of LED flicker
The impact and severity of flicker depends on the use caseand application. For slow speed applications, including back-up
camera systems or surround view systems, LED flicker of light
IS&T International Symposium on Electronic Imaging 2018
Autonomous Vehicles and Machines Conference 2018sources within the field of view will, in most cases, be mostly anannoyance or a distraction to the driver, because the driver will
typically have enough time to assess the situation. However, there
remains the possibility that the LED flicker will distract the driversufficiently to cause an accident. There is a separate scenario thatis also problematic for backup and surround view applications. If
a vehicle has PWM driven LED reversing lights, and is backing
up into a parking space, it is possible that banding effects, as seenin Figure 4, may occur. This can be potentially quite disturbing to
the driver. For high speed viewing applications, such as CMS (i.e.
rear view mirror replacement systems), PWM flicker has a greater
potential to cause accidents. As an illustrative example, consider
the scenario where a vehicle has a CMS system, and the driver ofthis vehicle is viewing a vehicle following behind. The trailing vehicle is equipped with LED headlamps. It is common for vehicle
LED headlamps to be driven by PWM signals with different frequencies and duty cycles. As a result, one headlamp may flicker
at a slow rate (e.g. ≤0.1Hz), whereas the other headlamp may
flicker at a faster rate (e.g.≈0.5Hz). In this scenario, it may easily
appear to a driver that the trailing vehicle has engaged their turnsignal indicators. The driver may incorrectly assume the trailing

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vehicle intends to change lane or make a turn. This misinterpretation of the scenario has obvious potentially hazardous consequences. Similarly, there have been anecdotal reports of drivers
misinterpreting a trailing car for an emergency vehicle (e.g. a police car) with its warning lights on. This scenario can occur if thePWM driven lights flicker at a higher rate, e.g. ≥5Hz. It has been
observed that drivers changed lanes or made way for a trailing vehicle, under the false assumption that it was an emergency vehicle. PWM flicker also has a potentially very significant impact on
ADAS and autonomous driving applications. PWM LED lights
are increasingly used for traffic signals and other traffic signs, including variable speed signs, road works signs etc. PWM flicker
may cause misdetection or non-detection of traffic signs, again
with potentially very hazardous implications.

The background may be a reflective target, as shown in Figure 10,
or may alternatively be a backlit tranmissive target.

LED flicker mitigation
LED flicker mitigation is a complex topic. There is currently
no consensus within the automotive imaging industry as to whatlevel of mitigation is required. As a general rule, a most applications would require that a light source should never appear to be”OFF” when imaged by a camera. This can be achieved by ensuring the camera exposure time is greater than or equal to the periodof the PWM light (i.e. as described in Equation 2). However, unless the exposure time of the camera is an exact integer multipleof the frequency of the PWM light source, the brightness of thelight will vary over time (Figure 3). In real world applications, it
is practically impossible to achieve this, because there PWM frequencies are not standardized. There are standards in place which
define the minimum frequency that can be used for road signs [1]to avoid visible flicker (90Hz or greater). This means that in any
given scene, there may be multiple LED lights within the camera
FoV, all operating at different frequencies. Setting a minimum
exposure time to PWMfreq also introduces other difficulties. For
example, to prevent a light from appearing ”OFF” for frequencies greater than 90Hz, a minimum exposure time of 11.111ms isrequired. In bright daylight scenes, almost all standard image sensors will overexpose if the exposure time is this long. A number of
sensor companies have developed new pixel architectures to allow
for longer exposure times without saturating. A review of these
designs is beyond the scope of this paper. It has been observed,
however, that increasing exposure time to mitigate LED flicker
exacerbates motion blur [3]. This can be especially problematicfor ADAS algorithms. For example, motion blur can make traffic
signs unreadable.

LED flicker measurement
There are currently no standards for LED flicker metrics andmeasurement procedures. This is being address as part of theIEEE P2020 working group on automotive image quality standards. It is critical that the laboratory test should be robust andaccurately reflect a camera system’s performance in real world
scenarios. This section reviews a proposal for a testing procedureand metrics for measuring LED flicker in a laborartory setting.

Test Setup
The proposed test setup is outlined in Figure8. A PWM
driven light is placed in front of a camera under test. A uniformly
illuminated target is present in the background, ideally 18% neutral grey, illuminated by a constant/non-modulating light source.

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Figure 8.

Test setup for flickering within an area illuminated by apulsed/modulated light source. 1 - uniform background, 2 - constant lightsource illuminating background (note: a backlit target is an acceptable alternative), 3 - camera under test, 4 - baffling to isolate background illuminationfrom camera FoV, 5 - PWM driven light, directly in the FoV of the camera
under test

The modulated light source should have variable frequency(50Hz to at least 1kHz recommended) and duty cycle (5%-100%).
The modulated light source may fill anywhere from 10% to 100%of the vertical field of view of the device. The light source should
be uniform, and ideally should have the same colour temperatureas the background illumination. The light source need not be infocus. The background illumination should be controllable, tosimulate both daylight and lowlight conditions. This is required,because the manifestations of flicker vary depending on the exposure time and/or HDR scheme of the camera under test. During initial trials, lowlight conditions were simulated by setting thebackground illumination to 40lux. Daylight conditions may besimulated by setting the background illumination to 2000lux. For
each frequency and duty cycle combination tested, the following
sequence was used:
1. Two seconds - light on with 100% duty cycle
2. Two seconds - light off (reference ”OFF” level for light)
3. Sixty seconds - light driven by PWM signal
Ideally, the luminance of the light during the initial 2 second”ON” period should match the luminance level during the 60 second PWM phase. This will require tuning of the voltage applied
to the LED lights for each phase of the test.

LED flicker metrics
To assess LED flicker, two different metrics were used. The
goal of the first metric is to determine whether or not the LED
light appears ”OFF” at any stage during testing. The metric chosen was based on the Weber contrast metric, where:
Flicker Dectection Index =min(LPW M ) − LOFF
LOFF

(3)

where min(LPWM ) is the minimum measured luma during
the 60 second period where the light is driven by the PWM signal, and LOFF is the measured luma during the 2 second ”OFF”
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period. In principle, if the light appears ”OFF”, then min(LPWM )= LOFF i.e. the minimum luma value during the PWM test period will be the same as the luma level during the baseline ”OFF”
period. In practice, there is typically some hysteresis in camera
automatic exposure/gain controls. Therefore, a tolerance of 10%
was added i.e. if the Flicker Detection Index is less than 0.1, it
is assumed that the light appears ”OFF”. As a general rule, ahigh Flicker Detection Index indicates good LED flicker mitigation performance.
A second metric, Percent Flicker, was also used, which was
based on Michelson contrast:
Percent Flicker =max(LPW M ) − min(LPW M )∗ 100max(LPW M ) + min(LPW M )(4)

The purpose of the Percent Flicker metric is to measure theresidual modulation in luma, in scenarios where the exposure timeis greater than 1\PWMfreq (see Equation 2). As a general rule, alow Percent Flicker score indicates good LED flicker mitigation.

some point the light would definitely appear ”OFF”. 150Hz waschosen because it is greater than the minimum exposure time of
the camera. In this case, the light would never appear ”OFF”, butthere will be some residual brightness modulation, which can bemeasured using Equation 4.

Results
Test results are shown in Figure 10 and Table 1. At 60Hz,
Flicker Detection Index is less than 0.1, indicating the light appeared ”OFF” in the video. In contrast, Flicker Detection Index is0.75 during the 150Hz, indicating the light always appears ”ON”.
In this example the residual modulation is also quite low, as indicated by the Percent Flicker of 1%. The fact that the Flicker
Detection Index is negative during the 60Hz test reflects the factthat there is hysteresis in the camera exposure control - the exposure and gain levels do not return to the exact same values after
the light toggles on and off at the start of the test.

Test setup validation
The test setup was validated using an automotive HDR camera. The camera under test was configured to mitigate flicker for
frequencies above 90Hz (i.e. the minimum exposure time was set
to 11.111ms). The camera was placed in the test setup as per Figure 8. Figure 9 shows a still image captured by the camera within
the test setup.
Figure 10.

Plot of luma (Y) for both 60Hz (top) and 150Hz (bottom). At

60Hz, it is clearly visible from the plot that the light appears ”OFF” approximately 40 frames. In contrast, the light appears more or less constant at
150Hz. There is, however, some residual modulation

Flicker Detection Index and Percent Flicker measured for 60Hz
and 200Hz

Frequency
60Hz
150Hz

Figure 9.

Image captured during LED flicker bench testing. The blue box

indicates the ROI chosen for measurement

The average luma value (Y) was calculated within the ROI
indicated by the blue rectangle (the ROI was 2 pixels high, 100
pixels wide). The shape of the ROI was chosen based on experience from development testing. The camera under test was arolling shutter design. When flicker does occur, it manifests asbands rolling up or down through the image. If the ROI weresquare, it would include some pixels where the light was ”ON”
and some where the light was ”OFF”. This would cause underestimation of min(LPWM ). Background illumunation was set to2000lux, to simulate a relatively bright scene. For this evaluation,
two test frequenies were used; 60Hz and 150Hz. A duty cycleof 20% was used for both tests. 60Hz was chosen because it isless than the minimum exposure time of the camera, therefore at
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Flicker Detection Index
-0.14
0.75

Percent Flicker
36
3

Figure 11 is an image taken during the 60Hz test. A darkband is visible in the middle of the light. The banding effect occurs because the sensor is a rolling shutter design - the dark bandcorresponds to the ”OFF” period of the PWM light. If the sensor
were a global shutter design, the entire light would appear ”OFF”.
In this example, the dark band rolls up through the image at a relatively slow rate. The height of the band, the rate of movementof the band and the direction of movement of the band all varydepending on the camera frame rate, PWM duty cycle and PWM
frequency.

Conclusions and Future Work
This paper summarizes the root cause of LED flicker, it’svarious manifestations, and potential impact for automotive applications. It also outlines a test setup, procedure and metrics
for assessing LED flicker for a given camera system. This test
setup has been shown to reliably indicate whether or not LED
flicker will occur for a given camera, depending on backgroundlight level, PWM frequency and duty cycle. Future work will ex-

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Figure 11.

Image captured during 60Hz test. A dark band is visible in the

middle of the light. The band is a rolling shutter effectpand on the results presented in this paper. Further testing andanalysis is required to validate the test setup and KPIs presented.
Further work will also have to be performed to define KPIs forthe banding effects as outlined in Figure 4. Further work will be
required to validate the metrics used in this paper. It is entirely
possible that frequency domain metrics may be more appropriate
and provide further insights. Psychophysical studies to correlate
objective metrics with subjective experience of flicker could also
prove useful. Initial work has also focused on rolling shutter sensors. The impact on global shutter sensors will also have to beassessed. Also, KPIs and metrics will also have to be defined toassess the impact of LED flicker on colour reproduction. This will
be particularly relevant for traffic sign recognition and similar algorithms. Ultimately, the results of these studies will be part of
the IEEE P2020 Automotive Image Quality standard.

References[1] EN12966:2014, European Standard for Variable Message Traffic
Signs (2014)[2] James Davis, Yi-Hsuan Hsieh, Hung-Chi Lee, Humans perceive
flicker at 500Hz, Scientific Reports (2015)[3] Tarek Lule, Challenges of HDR imaging in Automotive Environment,
AutoSens Brussels (2017)[4] Arnaud Darmont, High Dynamic Range Imaging: Sensors and Architectures (2012)

Author Biography
Brian Deegan received a PhD in Biomedical Engineering from the
National University of Ireland, Galway in 2011. Since 2011 he has
worked in Valeo Vision Systems as a Vision Research Engineer focusing on
Image Quality. His main research focus is on high dynamic range imaging, topview harmonization algorithms, LED flicker, and the relationshipbetween image quality and machine vision.

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Autonomous Vehicles and Machines Conference 2018